As mentioned earlier at this post, WealthTechs currently offer different APIs through which a user can connect and obtain data. Each of them has distinctive characteristics, and the choice of which tool to use is based on the technology it employs and the solutions it offers. This decision is also influenced by the complexity of the project into which the data will be integrated, its specific requirements, and the development team’s familiarity with each technology.
But if I already have a stable integration as a client, why should I consider switching to a new technology?
The answer lies in the normalization of current data and future system updates.
From our perspective, an essential aspect to consider when making a migration decision is not only the technology used in the new system but also the quality of information it possesses. If this improvement includes additional information, if this new version implies a reduction in operating costs, and if this new version will impact what products I can develop using it (reports, data analysis, applications), the conclusion is that yes, you should migrate.
In this section, we want to explain the changes that the new technology APIs (ODATA and GraphQL) brought to our database design and why they did so.
If we had to highlight one of the strongest features offered by these new technologies, it would undoubtedly be their ability to retrieve precise information through queries. This capacity to filter information and select and relate data that a client needs was one of the reasons that drove us to develop them. The goal was to give them control to access information efficiently. This significant yet subtle change made us reconsider whether our entity and relationship designs at the storage level were the most suitable and what improvements could be made in this regard. Because if a user can filter information, but it is disorganized and disconnected, we would lose the power of this feature due to the disorganization of information, making it more complex than necessary to obtain the data a client needs or leading to extended query times.
With this in mind, we proposed a database normalization for the V1 data schema.
But… what is database normalization?
Database normalization is a process in relational database management used to efficiently organize and structure data without redundancies. The primary goal of normalization is to eliminate data redundancy and ensure the integrity of stored information. This, in turn, helps maintain data coherence, making it easier to manage and query. Normalization enhances query performance, reduces data redundancy, and prevents data update and deletion problems that can arise in poorly structured databases.
In other words, while we made technical advancements in the technologies used in our API tools, we also made a remarkable improvement in data reorganization within our database. This is crucial to highlight because it not only benefits what can be achieved with each tool (filters, relationships, pagination, calculations) but also how this information is structured within each tool, in other words, a reorganization of data at a data level.
In this regard, we must emphasize that our V2 tools offer significant improvements. Every table, column, relationship, lookup, and key was thoroughly reviewed in this new data schema. Although the information is the same as in V1, the organization is more efficient, avoiding redundant data and establishing relationships between entities wherever possible. This enables the database engine to operate optimally due to the organized information.
To clarify, we want to emphasize that V2 currently does not offer additional information that is not available in V1 because the information remains the same. However, this information is now organized much more effectively, making the features of our new technologies operate much better and be more intuitive to use.
Making this change clear translates into reduced operating costs when accessing information, shorter loading times, better utilization of technology features for data access and operations, thus expanding the possibilities for integrating these tools and what can be achieved with them.
It’s also worth noting that within the V2 schema, it is now much easier to incorporate new information, so it is expected that over time, there will be an increase in the information currently available.
From the WealthTechs team, we can assure you that while the version change involves an investment in development time, it is strongly supported by the numerous benefits that this new version offers, both now and in the future.